What are we doing?

Daivd with his harp. (Unknown 960AD) Both Jewish and Christians scriptures contain very early religious music, partly said to be written by David.


Introduction

Music has been around since the history of mankind. However, where most of today’s music tends to be used for personal entertainment, it was often used to give praise to deities. But are there any musicological properties of a piece of music that make it specifically suitable for religious purpouses? Bach himself sometimes re-used his ‘pagan’ music for religious purposes and vice versa giving an important role to lyrics. However, we also know that Bach was a master in the writing of baroque affective music, indicating a carefull use of pitch, volume, tibre, and time for bringing music to it’s purposes. So, even if there is some overlap between musical sound of pagan and religious music, there might be some aspects which fit just better for one of them.

Method

To be able to answer the research question one has to compare religious music with non-religious music. This is implemented in R using the spotifyr module which gathers data from two types of playlists: religious and non-religious. Both corpuses are more usefull for machine learning purposes, as for example classification, if they contain many songs. Therefore, a set of different playlists which tend to be typically religious or non-religious has been made. Depending on the results, the religious playlists could be split up further to detect if there are any difference between different religions. Differences are measured between contemporary music lists but could be further expanded to more classical oriented music. Both sets are mostly biased with so called top-songs.

Data, data, data

Religious Playlist ID Songs Non-religious Complement Playlist ID Songs Balance
Religious 0IJbO5M2xD33mMHaeLRdSn 101 Non Religious 4VuiQ0wD6Xh5uDYveV2b0C 183 -97
Religious Songs 1Lfv5hpiBqtxHIlaeUo8TS 44 Non Religious 3 0B6Lj8siocfyTOCzyeBYzX 59
Christian Playlist for 2017 5t4HnPlX51s5ZdC2Lucnyz 391 Top 2017 1DoUPHRIAC6YbEPiDf8IOd 99 292
Top Christian Contemporary 37i9dQZF1DWUileP28ODwg 58 Today's Top Hits 37i9dQZF1DXcBWIGoYBM5M 50 8
Top Christian 37i9dQZF1DXcb6CQIjdqKy 66 TOP 2019 208tdAvqyrtssZFKLktwkx 43 23
Islamic Song 3SxT23r9nc6M1Ew2xrVpaV 108 Top Tracks of 2018 37i9dQZF1DX1HUbZS4LEyL 100 21
Islamic Songs 1YVnT9OowJP6ayM5QRazW7 120 Top of the Charts 7b2rMhQyuX3vkgQz2umhdV 107
Islamic / Nasheeds 1dNteyophghoFsbO3lCULn 67 Pop A Capella 6I3FnHFqsEwwifL63hX3gf 100 20
Fusion Hinduism 5lNmoVhBqIY0zKcZH3RZlr 53
Sanskrit / Hindu Mantra Chants 6RLNAQJoR5OUAl5lyA8YJJ 133 2019 Hits 4JkkvMpVl4lSioqQjeAL0q 128 5
Buddhist Meditation Songs 3c4AduB9UOrxkfdW0Nh2hA 270 Top allertijden 1nwCwjYUStN0xvoSmSgS9M 785 -22
BUDISTA 1aBpY65gFEM88trlD8Beht 238
Top Jewish Music 05Um5tgwbBWNAikYlwCId6 255
Jewish Music - Driving 1m0HB9PIDiovCDtO4qc00l 402 Driving Songs Everybody Likes 1prdy5Q62wxQ0Mb4gOOfeD 604 -202

Used playlists. Balance only compares the number of songs, not their duration. Playlist names might be altered and/or shortened for readability.


Inside the Box

  • We have got a total of 2209 unique religious songs, which means there are exactly 127 doubles in the set. [1]

  • The non-religious list makes up a total of 2310 unique non-religious songs, suprisingly enough there are no doubles here. [1]

  • The balance without removed duplicates equals 48 songs in favour of religious music. After data processing the balance alters to -101 in favour of non-religious. The difference in balanced based on songs and actual measure lies in the fact that sometimes not as many songs are gathered from a playlist a there should be. This might be due to a specific spotifyr implementation, but I have to further inverstigate that.

A few important notes

First of all, it is hard to tell whether all non-religious songs are really non-religous (considering that it also contains songs with titles as pray and faithfully) (1). Moreover, the data might be biased with pop-music (2). Furthermore, one could count for more duplicates based on title if one is willing to argue for a comparison on completly different kinds of music instead of counting different covers of the same song. (3). In addition, the quality of the complements is debatable. To keep it objective I used mainly meta-data like the title of a playlist to keep the musical features separate and measurable. One could also choose to complement based on a few musical features and look for differences on other features. However, there are still some vague matches. Religious and Non-religious seem intutively good complements where Buddhist Meditation Songs and Top allertijden look semantically further separated (4). Balanced is measured before removing duplicates. For higher accuracy balance should be computed after knowing how many songs from each playlist are gathered (but it can only count for one playlist). For balance the following measure is used (5):

balance = songs_religious - songs_non-religious


[1] Using the distinct function from R.

What’s inside?

spotify-features

spotify-features

Using the most interesting whole-song features from the Spotify API, duration_ms and speechiness are on a re-normalized log scale.


These visualisations show the spread of each musical variable. De cirle with cross shows where the mean lies. There are already some interesting findings visible like the difference in danceability of religious and non religious music. On average religious music is less danceable but more acoustic compared to non-religious music. Speechiness and duration are quite the same with exceptions to many outliers. On most properties Religious music has a very wide spread. Tempo is the same on average, however there is more spread in religious music.

The Key to Religion

Predicitions of the key of a piece of music according to Spotify. Keys are sorted on the most common of the whole corpus (both religious and non-religious music).


Using spotify’s key_mode property one is able to visualize how the keys are distributed for different religions. Religious songs tend to use a bit more of C major. Jewish music is using many different keys while Christian music follows the sorting order of the whole data set more general. Buddhist and Hindu music also seem quite diverse. However the total difference in religious and non-religious music is not that big. Maybe we can get more from a more emotional view of music?

Religions Differ

All songs from the corpus on the AV-plane, size is popularity.


On the arousal-valence plane religious and non-religious music have kind of the same spread, however there is a big difference for individual religions. Buddhistic music tends to be quite sleepy while most Jewish music tends to be very happy. Christian and Islamic music have a wider spread like non-religious music, where the former is in the more angry corner of the plane. The different musical modes do not have much influence on the emotional placement. These results point to a research direction which focuses more on different aspects of music of different religions. For now it seems that there is indeed a difference between religious and non-religious music. However it might also be that the differences are just the result of comparing western music with non-western music. To test that hypothesis Christian and Islamic songs have to be compared more thoroughly with the non-religious data set.

Outliers

Different aspects of an outlier.


Let’s inspect some outliers of different religions.

Archetypes

Different aspects of some archetypes.


These songs where selected based on their position on the AV-plane. They are closest to the mean of the energy and the mean of the valance of their group and represent the properties of a specific song central in their religious group.

TODO: interpretation

Learning Religions


Using Random Forest on the whole dataset we get the following results:

Predict Religion (cross = 5)

accuracy = 0.789
kappa = 0.689
j_index = 0.561

Loudness, energy and c_11 tend to be the most discriptive to discriminate between different religions.

Predict Type (cross = 10)

accuracy = 0.8649
kappa = 0.728
j_index = 0.728

c_11 tends to be very descriptive in the difference between religious and non-religious music. Also, in this corpus religious music seems tho consist of songs of a longer duration compared to non religious music.

So What?

Conclusion

There seems to be a lot of musical difference between different religions while for every religion there is some non-religious music available with kind of the same properties.

c_11 tends to be very descriptive in the difference between religious and non-religious music. Also, in this corpus religious music seems tho consist of songs of a longer duration compared to non religious music.


References

Burgoyne, J.A. 2019. “Computational Musicology Course Materials.” University of Amsterdam.

Plotly Technologies Inc. 2015. “Collaborative Data Science.” Montreal, QC: Plotly Technologies Inc. 2015. https://plot.ly.

Spotify. 2019. “Spotify Web Api.” 2019. https://developer.spotify.com/documentation/web-api/.

Unknown. 960AD. “David Playing His Harp.” Wikipedia.org. 960AD. https://en.wikipedia.org/wiki/Religious_music#/media/File:David-harp.jpg.

w3schools. 2019. “How to - Tabs.” 2019. https://www.w3schools.com/howto/tryit.asp?filename=tryhow_js_tabs.

Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. http://ggplot2.org.